A long-standing question in water research is the possibility that supercooled liquid water can undergo a liquid-liquid phase transition (LLT) in high and low density liquids. Studying this phenomenon in the lab is a bit impossible because water crystallizes into ice so quickly at such low temperatures.
That’s why scientists at the Georgia Institute of Technology use machine learning models to understand the phase changes of water. Thanks to this technique, scientists have found solid computational evidence supporting the liquid-liquid transition of water that can be applied to real-world systems that use water to operate.
To better understand the interaction between water, scientists used several complementary molecular simulation techniques. They ran molecular simulations on supercomputers, which Gartner compared to a virtual microscope. Their machine learning model is trained on density functional theory calculations with the SCAN exchange correlation function.
They carefully observed the movements of water molecules. At the same time, they characterized the fluid structure at different water temperatures and pressures, mimicking the phase separation between the high and low density fluids. (Scientists collected extensive data — running some simulations for up to a year — and continued to refine their algorithms for more accurate results.)
The researchers used a machine learning technique to determine the energy of the interactions between water molecules. This model dramatically accelerated the computation compared to conventional methods, which significantly improved the efficiency of the simulations.
Gartner said, “One of the challenges of this work is that there isn’t a lot of data to compare against, because it’s a problem that’s almost impossible to study experimentally. We’re pushing the boundaries here, so that’s another reason why it’s so important that we try to do this using multiple different computational techniques.”
Extremes that are unlikely to be present directly on Earth, but may occur in other aquatic habitats in the solar system, from the oceans of Europa to the water at the heart of comets, were some of the conditions the researchers evaluated. These discoveries could also help develop more accurate climate models and better understand the peculiar and complex physical chemistry of water and its uses in industrial activities.
Gartner said, “The work is even more generalizable. Water is a well-studied area of research, but this methodology could be extended to other hard-to-simulate materials such as polymers or complex phenomena such as chemical reactions.”
“Water is so central to life and industry, so this particular question of whether water can undergo this phase transition has been an issue for a long time. If we can move towards an answer, that’s important. But now we have this really powerful new computational technique, but we don’t know the limits yet, and there’s a lot of scope to move the field forward.”
Magazine reference:
- TE Gartner, III, PM Piaggi, R. Car, AZ Panagiotopoulos, PG Debenedetti, “Liquid-Liquid Transition in Water from First Principles”, *Phys. Rev. Lett., 2022. DOI: 10.1103/PhysRevLett.129.255702
